Trade Liberalisation and Economic Growth in ECOWAS Countries

Trade Liberalisation and Economic Growth in ECOWAS Countries ABSTRACT: This paper examines the effects of trade liberalization in forms of trade openness on economic growth in selected ECOWAS countries. More specifically, the idea is to examine the long run relationship between trade openness and growth in these countries. The study employs recent panel unit root tests and panel cointegration tests framework that allow for heterogeneity across selected countries using annual panel data on these countries. In particular, we implement several panel unit root tests (Maddala and Wu, 1999; Levin, Lin and Chu, 22; Im, Pesaran and Shin, 23) and panel cointegration tests (Pedroni, 1999, 24). Our estimation period covers from 198 to 28. Three different measures of openness are used in this study. The results from various panel unit root tests demonstrate that the panel data under consideration are stationary at first difference. Again, apart from the fact that the three core growth models employed (following different measures of openness) unarguably demonstrates that there exists long run relationship among the variables in the respective model, the panel cointegration regression result reveals that trade openness and liberalization are germane to growth prospect in the selected countries. This, therefore, lends credence to the growth-enhancing effects hypothesis of trade liberalization and openness in the ECOWAS countries. Hence, more trade enhancing policies through regional integration among member states in the ECOWAS would be beneficial for growth. Keywords: Trade liberalization, trade openness, economic growth, panel cointegration JEL Classification: C22, C23, F1, F15 1. Introduction For more than two decades, there have been different strands of theoretical and empirical studies aimed at investigating the relationship between trade liberalisation and growth both in developed and developing countries. The potential benefits of free trade, more specifically, those accruing from comparative advantage and specialization have been well documented in the classic theories of international trade (Krugman and Obstfeld, 211) 1. The traditional opinion of gains from globalization fundamentally rests on believe that when countries open up their economies, specialization and economic competitiveness are encouraged. However, changes that have occurred in the field of economic development and international trade in the last two decades, such as modification from inward-oriented policies to export-promoting strategy, are believed to have been majorly responsible for the vast and extensive empirical literature concerning trade openness and growth on the international scale. Also, the renewed emphasis on the need for regional trade integration and liberalization especially among developing countries has been argued to generally been traceable to the collapse in the multilateral trade agreements among nations in the World Trade Organisation. In fact, trade liberalisation has been a prominent component of policy advice to developing countries for the last two decades. Among the benefits claimed to spring from it, economic growth is probably the most important. Given 1 Concerted efforts by nations at establishing both bilateral trade links and subsequent formation of regional trading blocs, for instance EMU, NAFTA, MERCOSUR, SADC, GCC among others, are the upshot of this widely held view. 1

that free trade is fundamental to achieving the objective of regional trade agreement in most countries, especially the developing ones, trade liberalisation has often been implemented with the expectation of enhancing and promoting growth among countries (Greenaway et al., 22). Openness to trade has been seen as an important element of a sound economic policy and trade liberalization as a necessary element of achieving it 2. As the push for trade openness at the multilateral level becomes more and more contentious, various governments have been focusing on negotiating regional pacts as means to enhancing policy credibility and accelerating trade and investment liberalization in the hopes of spurring domestic growth. The fundamental rationale for this degree of commitment to programmes of trade reform is the obvious belief that liberalization is a pre-requisite to a transition from a relatively closed to a relatively open economy. For instance, it has been argued in the trade literature that export expansion is expected to lead to better resource allocation, economies of scale, production efficiency through knowledge and technological transfer, capital formation, employment creation and thus, economic growth and development (Author, 29). Export promotion, which is a product of trade liberalization, is also seen in most developing countries as a way of correcting imbalances in the external sector and at the same time assisting them in ensuring that their domestic economies made a full recovery. West African Countries are faced with just such a challenge in announcing creation of the Economic Community of West African States (ECOWAS). The effects of economic integration primarily on national output, among other economic fundamentals, have been rigorously and extensively research. More specifically, the attention of various empirical researchers has been focused on investigating the impact of trade liberalisation on different economies. This research upsurge, unarguably, is premised on the fact that economies the world over have become increasingly interdependent. While closer ties among nations has been partly driven by the rise in the movement of labour, services and capital- with the latter amid barriers to complete mobilityacross national borders, it is trade in goods that is arguably at the core of economic relations among independent states (Bahmani-Oskooee and Brooks, 1999). However, while there is a consensus that developing countries have a great deal to gain from free trade (Krueger, ; and ; Srinivasan and Bhagwati, 1999), a critical theoretical argument has also emerged that the sub-regional integration arrangements in Africa have failed to date to substantially increase trade (in terms of market access) and economic growth both within the region and in the world. Empirical studies which are mainly devoted to investigating growth enhancing effects of trade liberalization abound in the literature. For instance, Edwards (1993) provides a survey of trade and 2 Trade liberalization does not have a specific definition; nonetheless, some authors have attempted to define it. Shafaeddin (25) defines trade liberalization as any act that would make the trade regime more neutral -nearer to a trade system free of government intervention. Edwards () defines trade liberalization as any policy that reduces the degree of anti-export bias. 2

growth studies covering the 197s and 198s 3. In the empirical literature, the relationship between trade and economic growth has two distinct strands. First, the pre-199s studies focus on the relationship between exports and growth. With some qualifications, the regression analyses were consistent in their conclusions that growth of exports was significantly correlated with growth of output. Second, the post- 199s studies, such as Dollar (1992), Ben-David (1993), and Sachs and Warner (1995) focus on the relationship between openness and growth. These studies focus either on the direct impact of trade on output growth or total factor productivity growth (examples are Edwards, ; Coe et al, and Author, 29). Their results and hence policy intuitions, at best, are mixed. Several reasons emanating from different theoretical paradigm have been rigorously argued. Though this study aims at contributing to this ongoing empirical exercise with the eventual purpose of investigating the long run relationship between trade liberalization and growth in ECOWAS countries, its path is charted differently. The motivation for this study is centered on the need to examine the viability of trade performance in the light of growth dynamics in the ECOWAS region. One of the focal objectives of ECOWAS lies in the need to foster trade performance and growth not only among the country members but also with the rest of the world. It is expected, meanwhile, that this empirical exploration would not only help in guiding policy makers in formulating sound and more informed policies with respect to international trade performance, but also contribute immensely to the literature. Consequently, the overall objective of this paper is to investigate the long run relationship between trade liberalization on growth in the ECOWAS region employing different measures of openness. The remainder of this study is, therefore, structured as follows: While the issue of methodology involving data employed and model specification is extensively detailed in section 2, empirical analysis and results are presented in section 3. Finally, conclusion is made in section 4. 2. Methodology 2.1. Data Sources and Measurement With the overall aim of examining the impact of trade liberalization on growth in the ECOWAS region, this section delves into issues concerning data employed, study scope and model specification 3 The U.S. International Trade Commission, USITC () also provides a summary review of the literature on the dynamic effects of trade liberalization. 3

among other things. The variables used in this study include the following: real GDP per head; ratio of gross domestic investment to GDP; labour force participation rate; population growth rate; liberalization episode dummy and volumes trade openness measures 4. All variables are sourced from World Data Indicator (29) and the International Financial Statistics (various issues). The study scope ranges from 198 to 28 5. We employ annual panel data on 9 ECOWAS countries. The countries included in our analysis are: Burkina Faso, Cote d Ivoire, The Gambia, Ghana, Mali, Nigeria, Senegal, Sierra Leone and Togo. 2.2. Model Specification Given that over time, trade liberalization and growth especially in the developing countries have been subjected to rigorous empirical investigation and following recent developments in time series econometrics a number of authors have been able to model various determinants of core growth models augmented with indicators of trade liberalization and openness. Until now, these varied specifications reflect mainly differences in data employed and theoretical underpinnings. Following the work of Levine and Renelt (1992) which searched for a set of robust variables to model growth, most models include as explanatory variables the following: investment; population growth; initial per capita GDP; and initial human capital. Basically, this study shall employ the Aggregate Production Function (APF) framework. This production function which has been widely applied in the analysis of trade liberalization, trade openness and economic growth assumes unconventional inputs such as trade liberalisation and trade openness along the conventional inputs of labour and capital in the model. The approach used in this study follows that of Fosu and Magnus,. The aggregate growth model is thus specified thus: (1) From equation (1), Y t represents the aggregate production of the economy (proxied by GDP) at time t; A t, K t and L t also denote the total factor productivity (TFP), capital stock and labour stock at time t respectively. Consequently, TFP is therefore specified thus: (2) Hence, the model used in this study not only reflects theoretically enriched but also parsimonious specification models of core growth. In this study, the effect of trade liberalisation through the 4 One of the key difficulties in trying to assess the relationship between liberalisation and growth concerns an accurate measurement of the point at which a country is deemed to have liberalised. Clearly such a process does not happen instantaneously but it is possible to suggest when moves toward greater market freedoms occurred. The simplest option is to use a statement of intent, signals the beginning of reform. Thus, our first indicator of liberalisation is a dummy variable, which is activated at the time of a country s first World Bank intervention. 5 The choice of 198 to 28 is primarily due to the availability of data among the countries under investigation 4

introduction of structural adjustment policy in these countries is examined. Thus a dummy variable is included in (2) which thus become: (3) Therefore, to estimate [3], we take the natural logs of both sides which result in the following equation: (4) where = real GDP per head; = the ration of gross domestic investment to GDP; LABOR = labour force participation rate; = population growth rate; = liberalization episode dummy; = volumes trade openness measure. The term is the error term bounded with the classical statistical properties. Equation (4) is rightly represented within a panel setting by incorporating a subscript i depicting each of the countries in the sample. 3. Empirical Result and Interpretation As earlier stated, the overriding objective of this paper is to empirically examine the panel cointegration relationship among ECOWAS countries. For ease of rendition, this section presents the results of the methodological and analytical processes followed in this study. This section reports the results of time series and panel unit root tests on the data variables, panel cointegration tests. 3.1. Panel unit root test The starting point is to examine whether the variables under consideration contain a panel unit root. Table 1 displays the results of five distinct panel unit root tests, namely Levin, Lin, and Chu (LLC)'s t*, Breitung's t, Im, Pesaran, and Shin (IPS)'s W, and Maddala and Wu (MW)'s ADF- and PP- Fisher statistics on the level and first difference variables in our model. While LLC and Breitung, tests are based on the common unit root process assumption that the autocorrelation coefficients of the tested variables across cross sections are identical, IPS and ADF- and PP-Fisher tests solely rely on the individual unit root process assumption that the autocorrelation coefficients vary across cross sections. Table 1 reports all the unit root tests applied to all variables in our model for the panel of 9 ECOWAS countries. The results indicate that the variables contain a panel unit root. It is evident from our result that the null of panel unit roots cannot be rejected by LLC, Breitung, IPS, and both PP- and ADF-Fisher tests for all level variables under consideration. Thus, we may conclude that there exist unit roots in all the level variables considering the panel unit root test results. However, the result also indicates that all variables become stationary at first difference. Table 1: Panel Unit Root Result Common unit root process Individual unit root process 5

LLC t*-stat: Breitung-stat: IPS W-stat: ADF-Fisher: PP-Fisher: Variables Ho: unit root Ho: unit root Ho: unit root Ho: unit root Ho: unit root At 1 st At 1 st At 1 st At 1 st At 1 st At level At level At level At level At level Diff. Diff. Diff. Diff. Diff. Y.153..911..45..166..53. (Trade) (Import).998..973..354..76..1..91..999..931..991..836. 1...77.14.146..64..829..52..48..411..442..268..923..998..445..268..759..647..95..333..22... (Export) Notes: Figures in the Table are the statistics of 5 distinct panel unit root tests. Numbers in parentheses are marginal significance levels (p-values). *=significant at 1%, **=significant rejection of the null of unit roots at or below 5%. 3.2. Panel Cointegration Tests Panel cointegration primarily focuses on addressing whether there exists a long-run equilibrium relationship between the variables of interest if the variables contain a panel unit root. Hence, using Pedroni s (24) test that allows for heterogeneity in the intercepts and slopes of the cointegrating equation, we test for panel cointegration. Actually, Pedroni (24) provides seven statistics for the test of the null of no cointegration in heterogeneous panels. One group of tests is termed within dimension (panel tests) and the other group of tests is between dimension (group tests). The within-dimension tests take into account common time factors and allow for heterogeneity across countries. The betweendimension tests are group mean cointegration tests and allow for heterogeneity of parameters across countries. The seven Pedroni (24) panel cointegration test statistics that we employ are as follows: Within dimension (panel tests): (a) Panel v-statistic, (b) Panel Phillips Perron type r-statistics, (c) Panel Phillips Perron type t-statistic, (d) Panel augmented Dickey Fuller (ADF) type t-statistic. Between dimension (group tests): (e) Group Phillips Perron type r-statistics, (f) Group Phillips Perron type t- statistic, (g) Group ADF type t-statistic. These seven statistics are based on the estimated residuals from the following panel cointegration regression: Table 2: Pedroni s Panel Cointegration Test Result Test Statstics Model 1 Model 2 Model 3 Within dimension (panel tests) 6

v-statistic.574 (.2842) -2.72(.9776) -1.523(.9358) Phillips Perron t-statistic 1.5681 (.9416).4662(.6795).2259(.5894) Phillips Perron statistic -1.865 (.145) -1.6446**(.5) -2.272**(.136) ADF t-statistic -3.814** (.1) -2.624**(.46) -2.6164**(.44) Between dimension (group tests) Phillips-Perron -statistic 1.9855 (.9765) 1.31(.8487).9978(.848) Phillips Perron t-statistic -1.8366**(.331) -2.994**(.14) -2.9973**(.14) ADF t-statistic -3.441**(.3) -3.1756**(.7) -4.2755**(.) Notes: Probability values are in parenthesis; * and ** denote statistical significance at the 5 percent and 1 percent levels, respectively. Having established that all variables are stationary at first difference, we proceed to test whether there is a long run relationship between the variables using the Pedroni s (24) heterogeneous panel cointegration test. The idea is to examine whether there is a cointegration relationship between the dependent variable and explanatory variables for our models. The results for the seven different panel test statistics suggested by Pedroni are reported in Table 2. The statistical significance of these test statistics is provided in parenthesis in the form of p-values. Each of the seven-test statistics (with the exception of panel v and PP-t statistics) suggests that our growth models are exhibits long run cointegration relationship irrespective of the choice of trade openness used. 4. Summary and Conclusion As the push for trade openness at the multilateral level becomes more and more contentious, various governments have been focusing on negotiating regional pacts as means to enhancing policy credibility and accelerating trade and investment liberalization in the hopes of spurring domestic growth. The fundamental rationale for this degree of commitment to programmes of trade reform is the obvious belief that liberalization is a pre-requisite to a transition from a relatively closed to a relatively open economy. This study aims at contributing to this ongoing empirical exercise with the eventual purpose of investigating the long run relationship between trade liberalization and growth in ECOWAS countries. The motivation for this study is centered on the need to examine the viability of trade performance in the light of growth dynamics in the ECOWAS region. One of the focal objectives of ECOWAS lies in the need to foster trade performance and growth not only among the country members but also with the rest of the world. This paper examines the long run relationship between trade liberalization and economic growth in 1 ECOWAS countries. Hence, the study employs recent panel unit root tests and panel cointegration tests framework that allows for heterogeneity across selected countries using annual panel data on these countries. In particular, we implement several panel unit root tests (Maddala and Wu, 1999; Levin, Lin and Chu, 22; Im, Pesaran and Shin, 23) and panel cointegration tests (Pedroni, 1999, 24). Our estimation period covers from 198 to 28. Three different measures of openness are used in this study. The results from various panel unit root tests demonstrate that the panel data under consideration are 7

stationary at first difference. Again, the three core growth models employed (following different measures of openness) unarguably demonstrates there exists long run relationship among the variables in the respective models. This lends credence to the growth-enhancing effects hypothesis of trade liberalization and openness in the ECOWAS countries. Hence, more trade enhancing policies through regional integration among member states in the ECOWAS would be beneficial for growth. References Bahmani-Oskooee, M and Brooks, T.J. (1999): Bilateral J-curve between US and her trading partners, Weltwirtschaftliches Archiv, 135, 156-165. Baltagi, B. H. (25). Econometric Analysis of Panel Data (3rd ed.), Ch. 12. New York: John Wiley. Baltagi, B. H. and C. Kao (2). Nonstationary panels, cointegration in panels, and dynamic panels: a survey. Nonstationary Panels, Panel Cointegration, and Dynamic Panels. In B.H. Baltagi ed. Advances in Econometrics, vol. 15: 7-52. Amsterdam: JAI Press. Banerjee, A. (1999). Panel data unit roots and cointegration: an overview. Oxford Bulletin of Economics and Statistics (special issue, supplement), 61 (4): 67-629. 8

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Cote d'ivoire 197 199 22 Ghana 197 2 23 Krueger, A. () Why Trade Liberalisation Is Good For Growth. The Economic Journal, (18)45: 1513-1521 Krugman, P. and Obstfeld, M. (21) International Economics: Theory and Policy, 5 th ed., Addison- Wesley, New York. Levin, A., C-F. Lin, and C-S.J. Chu (22). Unit root tests in panel data: asymptotic and finite-sample properties. Journal of Econometrics, 18: 1-24. Maddala, G.S. and S. Wu (1999). A comparative study of unit root tests with panel data and a new simple test. Oxford Bulletin of Economics and Statistics, (special issue, supplement), 61 (4): 631-652. Author, O. (29) Export-Led growth hypothesis: Further econometric evidence from Nigeria Pakistan journal of social sciences 6(4): 219-223, 29 Pedroni (24). Panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to the PPP hypothesis. Econometric Theory, 2: 597-625. Pedroni, P. (1999). Critical values for cointegration tests in heterogeneous panels with multiple regressors. Oxford Bulletin of Economics and Statistics, 61 (4): 653-67. Pedroni, P. (2). Fully modified OLS for heterogeneous cointegrated panels. Nonstationary Panels, Panel Cointegration, and Dynamic Panels, in B.H. Baltagi ed. Advances in Econometrics vol. 15: 93-13. Amsterdam: JAI Press (Elsevier Science). Sachs, J. And A. Warner (1995) Economic Reform and the Process of Global Integration, Brookings Papers on Economic Activity 1. Shafaeddin M (25). Trade Policy at the Crossroads: The Recent Experience of Developing Countries. London, Palgrave MacMillan. Srinivasan, T.N., And J. Bhagwati (1999) Outward-Orientation and Development: Are the Revisionists Right? Economic Growth Center, Yale University: New Haven, Center Discussion Paper no 86. Appendix: Trends in Economic Growth and Trade in the Selected ECOWAS Countries 1.2E+1 1E+1 8E+9 6E+9 4E+9 2E+9 Growth Performance in ECOWAS Countries: Trend Analysis (197-28) 8E+9 6E+9 4E+9 2E+9 1

11 2 4 6 197 199 22 Gambia 2E+1 4E+1 6E+1 8E+1 197 2 23 Nigeria 5 1E+9 1.5E+9 2E+9 197 199 22 Sierra Leone 5 1E+9 1.5E+9 2E+9 197 199 22 Togo 2E+9 4E+9 6E+9 8E+9 197 199 22 Mali 2E+9 4E+9 6E+9 8E+9 197 2 23 Burkina Faso 5E+9 1E+1 1.5E+1 197 2 23 Senegal

12 Trade Performance in ECOWAS Countries: Trend Analysis (197-28) 5 1 15 197 2 23 Cote d'ivoire 5 1 15 197 2 23 Ghana 5 1 15 197 2 23 Gambia 2 4 6 8 1 12 197 2 23 Nigeria 2 4 6 8 197 2 23 Sierra Leone 5 1 15 2 25 3 197 2 23 Togo 5 1E+9 1.5E+9 197 199 22 Mali 2 4 6 8 197 199 22 Burkina Faso 5 1E+9 1.5E+9 2E+9 197 199 22 Senegal